FreeCourse Logo
FreeCourse.io
Verified CouponsFree CoursesJobsBlog
Categories
Home/Courses/AI Development with Qwen 2.5 & Ollama: Build AI Apps Locally
AI Development with Qwen 2.5 & Ollama: Build AI Apps Locally
Development100% OFF

AI Development with Qwen 2.5 & Ollama: Build AI Apps Locally

Udemy Instructor
4.4(9.8K students)
Self-paced
All Levels

About this course

Are you ready to build AI-powered applications locally without relying on cloud-based APIs? This hands-on course will teach you how to develop, optimize, and deploy AI applications using Qwen 2. 5 and Ollama, two powerful tools for running large language models (LLMs) on your local machine.

With the rise of open-source AI models, developers now have the opportunity to create intelligent applications that process text, generate content, and automate tasks—all while keeping data private and secure. In this course, you’ll learn how to install, configure, and integrate Qwen 2. 5 with Ollama, build FastAPI-based AI backends, and develop real-world AI solutions.

Why Learn Qwen 2. 5 and Ollama? Qwen 2.

5 is a powerful large language model (LLM) developed by Alibaba Cloud, optimized for natural language processing (NLP), text generation, reasoning, and code assistance. Unlike traditional cloud-based models like GPT-4, Qwen 2. 5 can run locally, making it ideal for privacy-sensitive AI applications.

Ollama is an AI model management tool that allows developers to run and deploy LLMs locally with high efficiency and low latency. With Ollama, you can pull models, run them in your applications, and fine-tune them for specific tasks—all without the need for expensive cloud resources. This course is practical and hands-on, designed to help you apply AI in real-world projects.

Whether you want to build AI-powered chat interfaces, document summarizers, code assistants, or intelligent automation tools, this course will equip you with the necessary skills. Why Take This Course? - Hands-on AI development with real-world projects- No reliance on cloud APIs—keep your AI applications private & secure- Future-proof skills for working with open-source LLMs- Fast, efficient AI deployment with Ollama’s local executionBy the end of this course, you'll have AI-powered applications running on your machine, a deep understanding of LLMs, and the skills to develop future AI solutions.

Are you ready to start building?

Skills you'll gain

Data ScienceEnglish

Available Coupons

Loading...

Course Information

Level: All Levels

Suitable for learners at this level

Duration: Self-paced

Total course content

Instructor: Udemy Instructor

Expert course creator

This course includes:

  • 📹Video lectures
  • 📄Downloadable resources
  • 📱Mobile & desktop access
  • 🎓Certificate of completion
  • ♾️Lifetime access
$0$98.99

Save $98.99 today!

Enroll Now - Free

Redirects to Udemy • Limited free enrollments

Share this course

https://freecourse.io/courses/ai-development-with-qwen-ollama-build-ai-apps-locally

You May Also Like

Explore more courses similar to this one

Deep Learning A-Z: Build Neural Networks & TensorFlow
Development
0% OFF

Deep Learning A-Z: Build Neural Networks & TensorFlow

Udemy Instructor

Deep Learning is transforming industries—from healthcare and finance to autonomous vehicles and generative AI. In this comprehensive course, you’ll go step by step through the foundations and advanced concepts needed to build powerful neural networks using TensorFlow and Python. Whether you're a beginner or an aspiring AI professional, this course is designed to take you from zero to job-ready with hands-on, practical learning.I start by building a strong foundation in neural networks. You’ll understand how deep learning works under the hood—without unnecessary complexity. Concepts like perceptrons, activation functions, loss functions, gradient descent and backpropagation are explained clearly and visually, so you truly grasp what’s happening inside the model.Next, you’ll move into practical implementation using TensorFlow. Instead of just watching theory, you’ll build models from scratch and train them on real datasets. By writing code line by line, you’ll gain the confidence to design, train, evaluate and optimize neural networks on your own projects.You’ll explore powerful deep learning architectures used in real-world applications. You’ll work with Convolutional Neural Networks (CNNs) for computer vision, Recurrent Neural Networks (RNNs) for sequence data, and modern techniques that improve model accuracy and performance. Each concept is reinforced with hands-on coding exercises.You’ll also learn how to improve model performance using regularization, dropout, batch normalization and hyperparameter tuning. Understanding these techniques is what separates beginners from true deep learning practitioners. By the end, you won’t just know how to build models—you’ll know how to make them better.Throughout the course, you’ll complete practical projects that simulate real industry scenarios. These projects are designed to strengthen your portfolio and help you apply your skills in real-world environments.This course is ideal for students, developers, data analysts, and aspiring AI engineers who want a structured, practical path into deep learning. Basic Python knowledge is recommended, but no prior deep learning experience is required. By the end of this course, you’ll have the knowledge, confidence and hands-on experience to build advanced deep learning systems from scratch.

0.0•1.8K•Self-paced
FREE$90.99
Enroll
AI & Quantum Computing Mastery: From Zero to Expert Bootcamp
Development
0% OFF

AI & Quantum Computing Mastery: From Zero to Expert Bootcamp

Udemy Instructor

Unlock the power of Artificial Intelligence (AI) and Quantum Computing (QC) with this comprehensive, hands-on course designed for absolute beginners and professionals looking to explore the next generation of computing technologies. This course covers Machine Learning (ML), Deep Learning (DL), Neural Networks, Quantum Mechanics, Quantum Machine Learning (QML), and Hybrid AI-QC Applications, equipping you with the skills to build real-world projects.As AI continues to transform industries like healthcare, finance, cybersecurity, and automation, Quantum Computing is revolutionizing the way we solve complex problems through superposition, entanglement, and quantum gates. This course is structured to help you master AI fundamentals before diving into Quantum Algorithms, Quantum AI, and Hybrid AI-QC Systems. Why Take This Course?Learn AI, Machine Learning, Deep Learning, and Neural Networks from scratch.Understand Quantum Computing principles including Qubits, Superposition, Entanglement, and Quantum Circuits.Master Quantum Machine Learning (QML) with Quantum Neural Networks (QNNs) and Quantum Optimization.Gain hands-on experience with TensorFlow, PyTorch, Qiskit, IBM Quantum, and OpenAI.Implement Quantum-powered applications for drug discovery, finance, and portfolio optimization.Develop expertise in AI-powered quantum simulations to accelerate big data analytics and deep learning.What You Will Learn:AI & Machine Learning FundamentalsIntroduction to Artificial Intelligence, Supervised & Unsupervised Learning.Hands-on Deep Learning with TensorFlow & PyTorch.Develop AI-powered chatbots, image recognition, and fraud detection models.Implement Reinforcement Learning for self-learning AI systems.Quantum Computing & Quantum AlgorithmsUnderstand Quantum Bits (Qubits), Quantum Gates, Quantum Superposition & Entanglement.Learn Quantum Circuit Design & Quantum Measurement.Implement Quantum Algorithms like Grover’s Search, Shor’s Algorithm, and Variational Quantum Classifiers (VQC).Quantum Machine Learning (QML) & AI-QC Hybrid ApplicationsExplore Quantum-enhanced AI, Quantum Kernel Methods, and Variational Quantum Circuits.Train Quantum Neural Networks (QNNs) for deep learning tasks.Implement Quantum-enhanced ML models for finance, drug discovery, and cybersecurity.Who Should Take This Course?Beginners looking to master AI, Machine Learning, Deep Learning & Quantum Computing.Software Developers & Data Scientists interested in Quantum AI & Hybrid AI-QC Applications.AI Researchers & Quantum Computing Enthusiasts exploring Quantum Neural Networks & QML.Tech Professionals wanting to transition into Quantum Computing & AI Research.Technologies CoveredPython, TensorFlow, PyTorch, OpenAI, IBM Quantum, Qiskit, D-Wave, Scikit-Learn, NumPy, PandasQuantum Algorithms, Quantum Neural Networks, Variational Quantum Circuits, Quantum CryptographyReinforcement Learning, Natural Language Processing (NLP), AI for Cybersecurity, AI for Healthcare, AI for FinanceThis course provides everything you need to become an AI & Quantum Computing expert, ensuring you're ready for the future of AI-powered Quantum Computing.

4.3•8.8K•Self-paced
FREE$100.99
Enroll
Mastering AI Agents Bootcamp: Build Smart Chatbots & Tools
Development
0% OFF

Mastering AI Agents Bootcamp: Build Smart Chatbots & Tools

Udemy Instructor

Artificial intelligence is transforming the way we work, automate tasks, and interact with technology. This course is designed to help learners build AI-powered agents, automation bots, chat assistants, and task management systems using open-source tools without relying on external APIs or cloud-based services. Whether you are a beginner exploring artificial intelligence or a developer looking to integrate AI into real-world applications, this course provides a hands-on approach to building AI-driven automation solutions.Throughout this course, learners will gain practical experience in developing intelligent assistants that can process text, respond to user queries, automate repetitive tasks, and manage workflows efficiently. The focus will be on implementing AI-powered chatbots, smart task managers, document readers, web scrapers, and personal productivity assistants. By leveraging local AI models, vector databases, and natural language processing techniques, students will learn how to create AI solutions that function entirely on their machines without any reliance on cloud APIs.The course starts with an introduction to AI agents, covering the fundamental concepts of natural language processing, automation workflows, and task execution. Learners will build chatbots capable of carrying on meaningful conversations while maintaining memory of past interactions. By integrating AI models with local vector databases such as FAISS, students will store and retrieve information efficiently, allowing their AI agents to answer complex queries based on stored knowledge. As the course progresses, students will develop AI-powered task automation bots capable of scheduling, organizing, and prioritizing tasks using machine intelligence.One of the key aspects of this course is building AI-driven document readers that extract, summarize, and provide answers from PDF files. Learners will implement an AI system that processes and retrieves relevant information, enabling intelligent document search and Q&A functionalities. Additionally, students will create an AI-powered web scraper that extracts text from websites, summarizes content, and stores valuable insights in a searchable vector database for later use. These AI automation techniques can be applied in various domains, including research, business intelligence, and content generation.As learners progress through the course, they will work on projects that integrate AI into daily productivity tools. They will develop personal AI assistants that help with scheduling, reminders, and workflow management. The course also covers AI-powered task prioritization, where students will train models to analyze deadlines and assign importance to different activities. By the end of the course, students will have a strong understanding of how to build AI agents capable of automating complex tasks, enhancing productivity, and managing data-driven workflows.This course is designed for software developers, data analysts, AI enthusiasts, and anyone interested in building AI automation solutions. No prior experience in artificial intelligence is required, as all concepts are introduced progressively with step-by-step implementations. Learners will gain hands-on experience with AI tools, machine learning models, and automation frameworks, making this course ideal for those who want to integrate AI into real-world applications. All projects are built using open-source software and executed locally, ensuring privacy, security, and full control over AI-driven automation systems.By the end of this course, students will have the knowledge and practical skills to create AI-powered chatbots, automation bots, document readers, web scrapers, and intelligent personal assistants. They will be equipped to develop AI solutions that streamline workflows, enhance productivity, and automate repetitive tasks efficiently. This course provides a solid foundation in AI-driven automation and equips learners with the ability to design, build, and deploy AI agents for various use cases.

0.0•9.7K•Self-paced
FREE$95.99
Enroll
FreeCourse LogoFreeCourse

Freecourse.io brings you high-quality online courses with free certificates to help you upskill, boost your career, and achieve your goals anytime, anywhere.

Resources

  • Courses
  • Jobs
  • Categories
  • Features

Company

  • About
  • Blog
  • Contact

Legal

  • Privacy
  • Terms
  • Cookies
  • Licenses

© 2026 FreeCourse. All rights reserved.